'On-the-Fly Field-potential Sensing Electrode Track' (OFFSET) based NSC sorting for brain research. Abstract: The past decade has acquired a profound paradigm shift in high throughput tools for brain research with the advent of programming techniques in micro/nano systems, stem cells, signal processing and genomics. One area in which these technologies have opened new avenues has been the application of pluripotent stem cells to study neurodegenerative diseases. The derivation of patient-specific reprogrammed somatic cells enables immunologically compatible viable brain tissue for use in studying disease development, creating therapies for neurological disorders and developing perfect models for the cells of the central nervous system that are harmed in the diseases. The major challenge in translating stem cell biology into such useful tissue is the establishment of effective separation methods to isolate differentiated cells and exclude cells that hinder graft performance or lead to teratoma formation. Unfortunately, conventional separation techniques for stem cells such as microscope-assisted manual isolation, FACS and MACS require intensive labor, exogenous labeling or genetic modification is not suitable for such clinical applications. Therefore, Biopico Systems teams with the researchers from University of California, Irvine for their expertise in microfluidics, the Children's Hospital of Orange County (CHOC) Research Institute for their expertise in iPS cells therapy, and Arizona State University for their expertis in neuronal stimulus recording using microelectrode array in order to demonstrate the technical feasibility of a label-free electrical field potential marker based cell sorting for brain research With our understanding of the practical constraints of the system components from the laboratories of our collaborators, we propose to develop complex therapeutic technology for research and practice. We envision developing a family of systems to sort neural stem cells for several applications to lead technological transformation in neuroscience.